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WIRELESS AUTOMATIC GARAGE DOOR CONTROLLER MENGGUNAKAN NODEMCU ESP8266 Hartana Hartana
CONTEN : Computer and Network Technology Vol. 3 No. 1 (2023): Juni 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/conten.v3i1.2001

Abstract

Penelitian ini bertujuan untuk mengembangkan Wireless Automatic Garage Door Controller menggunakan NodeMCU ESP8266. Sistem ini memungkinkan pengguna untuk mengoperasikan pintu garasi secara nirkabel melalui jaringan WiFi. Selain itu, sistem ini dilengkapi dengan sensor jarak ultrasonik untuk mendeteksi keberadaan kendaraan atau obyek di sekitar pintu garasi. Metode penelitian yang digunakan adalah desain penelitian eksperimental yang melibatkan pengujian fungsionalitas sistem dan evaluasi performa pengendalian pintu garasi otomatis. Data dikumpulkan melalui survei kuesioner dan pengamatan langsung terhadap penggunaan sistem. Hasil penelitian menunjukkan bahwa sistem Wireless Automatic Garage Door Controller berhasil diimplementasikan dengan baik. Pengujian fungsionalitas menunjukkan bahwa sistem dapat membuka dan menutup pintu garasi secara otomatis serta mendeteksi keberadaan kendaraan atau obyek dengan akurat. Analisis data menggunakan metode statistik deskriptif menunjukkan bahwa pengguna cenderung menggunakan sistem dengan frekuensi yang sedang. Rata-rata penggunaan sistem adalah 3.36 dan standar deviasinya adalah 1.06. Sistem ini memiliki keunggulan dalam kemudahan pengoperasian melalui antarmuka yang user-friendly dan keamanan yang baik melalui fitur keamanan tambahan. Selain itu, sistem ini responsif, efektif, dan efisien dalam pengendalian pintu garasi. Dalam kesimpulan, Wireless Automatic Garage Door Controller menggunakan NodeMCU ESP8266 memberikan hasil positif dalam pengendalian pintu garasi. Sistem ini dapat mengendalikan pintu garasi dengan baik, merespons perintah dengan cepat, dan mendeteksi keberadaan kendaraan atau obyek secara akurat.
Implementation Of Decision Tree Algorithm For Classification Of Eligibility In Social Assistance Fund Distribution Raden Deasy Mandasari; Hartana Hartana
TIERS Information Technology Journal Vol. 5 No. 1 (2024)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v5i1.5378

Abstract

This study examined the use of decision tree algorithms, specifically C4.5, in classifying the eligibility for social assistance fund distribution in Kelurahan Bangka Belitung Laut, Kecamatan Pontianak Tenggara. Inaccuracies in distribution were caused by recipient selection based on village officials' recommendations, which only considered the type of occupation. To address this issue, this study developed a system based on the C4.5 algorithm to process economic census data. This research used a quantitative method with a descriptive analytical approach, collecting data through literature studies and economic census, and processing data using the Rapid Miner application. The classification model generated was evaluated using 10-fold cross-validation to ensure high accuracy. The results showed that the C4.5 algorithm achieved 100% accuracy, precision, and recall. The decision tree model indicated that the main attributes determining eligibility were occupation and income. Some rules derived from this model, such as those who are unemployed with an income below Rp29,500 being eligible for assistance, provided clear guidelines for policymakers. The implementation of this algorithm is expected to improve fairness and effectiveness in the distribution of social assistance funds in Kelurahan Bangka Belitung Laut, reduce public dissatisfaction, and prevent potential social conflicts. This study recommended adopting the model in other areas with adjustments to local data to enhance broader fairness in aid distribution.
Inovasi Parkir Cerdas: Prediksi Posisi Kendaraan dengan Teknologi RFID dan Arduino Mega 2560 R3 Raden Deasy Mandasari; Hartana Hartana
Jurnal Teknik Elektro Uniba (JTE UNIBA) Vol. 9 No. 1 (2024): JTE UNIBA (Jurnal Teknik Elektro Uniba)
Publisher : Lembaga Penelitian Universitas Balikpapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36277/jteuniba.v9i1.235

Abstract

Urban parking management is an urgent challenge in an ever-increasing vehicle mobility era. This research develops an intelligent parking system that integrates RFID (Radio-Frequency Identification) technology and Arduino Mega 2560 R3 to predict the vehicle's position in real time. The initial literature study identified various approaches to parking management, but none comprehensively combined RFID and Arduino Mega 2560 R3. Therefore, this study fills this gap. The research method involves literature study, system design, hardware and software development, and field testing. In the proposed system, vehicles are equipped with RFID cards, and the parking infrastructure is equipped with RFID readers. When the vehicle enters the parking area, the system reads the RFID card and predicts available parking positions. The results of field tests show an increase in the efficiency of parking space use of around 37% to 46%, and the accuracy of parking position prediction is above 90%. This research provides effective solutions for urban parking management, reducing traffic congestion and air pollution. This system also increases the driver's comfort in finding a suitable parking space. Thus, this research has the potential to support more sustainable urban development by optimizing the use of parking lots and reducing the negative impact of motorized vehicles in urban areas.